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Pretrained large language models (LLMs) have consistently shown state-of-the-art performance across multiple natural language processing (NLP) tasks. These models are of much interest for a variety of industrial applications that use NLP as a core ...

We propose to accelerate use-inspired basic research in causal AI through a suite of causal tools and libraries that simultaneously provides core causal AI functionality to practitioners and creates a platform for research advances to be rapidly ...

Commercially sold electrical or gas products must comply with the safety standards imposed within a country and get registered and certified by a regulated body. However, with the increasing transition of businesses to e-commerce platforms, it becomes ...

Online marketplaces are able to offer a staggering array of products that no physical store can match. While this makes it more likely for customers to find what they want, in order for online providers to ensure a smooth and efficient user experience, ...

NLU models power several user facing experiences such as conversations agents and chat bots. Building NLU models typically consist of 3 stages: a) building or finetuning a pre-trained model b) distilling or fine-tuning the pre-trained model to build ...

With the rapidly growing AI market opportunities and the accelerated adoption of AI technologies for a wide range of real-world applications, responsible AI has attracted increasing attention in both academia and industries. In this talk, I will focus ...

Understanding student behavior patterns is fundamental to building smart campuses. However, the diversity of student behavior and the complexity of educational data not only bring great obstacles to the relevant research, but also leads to unstable ...

Audit issues summarize the findings during audit reviews and provide valuable insights of risks and control gaps in a financial institute. Despite the wide use of data analytics and NLP in financial services, due to the diverse coverage and lack of ...

In this technical demonstration, we present SMILEY, a voice-guided virtual assistant. The system utilizes a deep neural architecture ContraCLIP to manipulate facial attributes using voice instructions, allowing for deeper speaker engagement and smoother ...

Time series forecasting is an important ingredient in the intelligence of business and decision processes. In industrial scenarios, the time series of interest are mostly macroscopic time series that are aggregated from microscopic time series, e.g., ...

The black-box nature and the lack of interpretability detract from constant improvements in Graph Neural Networks (GNNs) performance in social network tasks like friendship prediction and community detection. Graph Counterfactual Explanation (GCE) ...

In this paper, we present a framework to deal with the fraud detection task with extremely few labeled frauds. We involve human intelligence in the loop in a labor-saving manner and introduce several ingenious designs to the model construction process. ...

Hate speech is a challenging problem in today's online social media. One of the current solutions followed by different social media platforms is detecting hate speech using human-in-the-loop approaches. After detection, they moderate such hate speech ...

Graph neural networks (GNNs), which extend deep learning models to graph-structured data, have achieved great success in many applications such as detecting malicious activities. However, GNN-based models are vulnerable to camouflage behavior of ...

Graphs are ubiquitous, which makes machine learning on graphs an important research area. While there are many aspects to this field, our research is focused primarily on two aspects of it. The first research question concerns privacy in graphs, where ...

Hateful content is a growing concern across different platforms, whether it is a moderated platform or an unmoderated platform. The public expression of hate speech encourages the devaluation of minority members. It has some consequences in the real ...

In the big data era, the relationship between entities becomes more complex. Therefore, graph (or network) data attracts increasing research attention for carrying complex relational information. For a myriad of graph mining/learning tasks, graph neural ...

Conversational agents, or commonly known as dialogue systems, have gained escalating popularity in recent years. Their widespread applications support conversational interactions with users and accomplishing various tasks as personal assistants. However,...

With the availability of massive labeled training data, powerful machine learning models can be trained. However, the traditional I.I.D. assumption that the training and testing data should follow the same distribution is often violated in reality. ...

Social media sites such as Twitter and Facebook have connected billions of people and given the opportunity to the users to share their ideas and opinions instantly. That being said, there are several negative consequences as well such as online ...